A Proposal to Distinguish State Dependence and Unobserved Heterogeneity in Binary Brand Choice Models

This paper uses binary choice models that specify four possible sources of observed regularity in the consumer brand choice decision over purchase occasion: namely, state dependence, observed and unobserved heterogeneity and correlation effects. The objective is to distinguish correctly among the effects of these four variables. The estimation method proposed is an alternative to the most commonly used estimation methods in marketing choice models. We consider that the alternative method appropriately controls for observed heterogeneity and unobserved heterogeneity correlated with the state dependence variable because of the way the state dependence variable is built. The model is used for the first time in marketing following the methodology proposed by Chamberlain (1984). A relationship for unobserved heterogeneity is specified, taking into account the correlation among unobserved heterogeneity and other choice determinants. In this way, we split the influence of household state dependence and tastes on brand choice. The findings are very conclusive. We find that because the individual effects and the covariates are correlated, traditional estimation methods cannot be used to split state dependence and unobserved heterogeneity. The proposed model is found to yield better measures of predictive performance than the conventional model. The results are found to be robust across categories of laundry detergent and have significant implications for marketing policy.